Explanation oriented retrieval

  • Dónal Doyle
  • , Pádraig Cunningham
  • , Derek Bridge
  • , Yusof Rahman

Research output: Chapter in Book/Report/Conference proceedingsChapterpeer-review

Abstract

This paper is based on the observation that the nearest neighbour in a case-based prediction system may not be the best case to explain a prediction. This observation is based on the notion of a decision surface (i.e. class boundary) and the idea that cases located between the target case and the decision surface are more convincing as support for explanation. This motivates the idea of explanation utility, a metric that may be different to the similarity metric used for nearest neighbour retrieval. In this paper we present an explanation utility framework and present detailed examples of how it is used in two medical decision-support tasks. These examples show how this notion of explanation utility sometimes select cases other than the nearest neighbour for use in explanation and how these cases are more convincing as explanations.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPeter Funk, Pedro A. Gonzalez-Calero
PublisherSpringer Verlag
Pages157-168
Number of pages12
ISBN (Print)3540228829, 9783540228820
DOIs
Publication statusPublished - 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3155
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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